Papers
A Novel Two-Step Method for Cross Language Representation Learning
Min Xiao, Yuhong Guo
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs
Vikash K Mansinghka, Tejas D Kulkarni, Yura N Perov et al.
Approximate Dynamic Programming Finally Performs Well in the Game of Tetris
Victor Gabillon, Mohammad Ghavamzadeh, Bruno Scherrer
Approximate Gaussian process inference for the drift function in stochastic differential equations
Andreas Ruttor, Philipp Batz, Manfred Opper
Approximate Inference in Continuous Determinantal Processes
Raja Hafiz Affandi, Emily B. Fox, Ben Taskar
Approximate inference in latent Gaussian-Markov models from continuous time observations
Botond Cseke, Manfred Opper, Guido Sanguinetti
A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks
Junming Yin, Qirong Ho, Eric P Xing
A simple example of Dirichlet process mixture inconsistency for the number of components
Jeffrey W Miller, Matthew T Harrison
A Stability-based Validation Procedure for Differentially Private Machine Learning
Kamalika Chaudhuri, Staal A Vinterbo
Auditing: Active Learning with Outcome-Dependent Query Costs
Sivan Sabato, Anand D Sarwate, Nati Srebro
Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions
Ari Pakman, Liam Paninski
Bayesian entropy estimation for binary spike train data using parametric prior knowledge
Evan W Archer, ll Memming Park, Jonathan W Pillow
Bayesian Hierarchical Community Discovery
Charles Blundell, Yee Whye Teh
Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC
Roger Frigola, Fredrik Lindsten, Thomas B Schön et al.
Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits
Ben Shababo, Brooks Paige, Ari Pakman et al.
Bayesian inference as iterated random functions with applications to sequential inference in graphical models
Arash Amini, Xuanlong Nguyen
Bayesian inference for low rank spatiotemporal neural receptive fields
Mijung Park, Jonathan W Pillow
Bayesian Mixture Modelling and Inference based Thompson Sampling in Monte-Carlo Tree Search
Aijun Bai, Feng Wu, Xiaoping Chen
Bayesian optimization explains human active search
Ali Borji, Laurent Itti
Bellman Error Based Feature Generation using Random Projections on Sparse Spaces
Mahdi Milani Fard, Yuri Grinberg, Amir-massoud Farahmand et al.
Beyond Pairwise: Provably Fast Algorithms for Approximate $k$-Way Similarity Search
Anshumali Shrivastava, Ping Li
BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables
Cho-Jui Hsieh, Matyas A Sustik, Inderjit S Dhillon et al.
Binary to Bushy: Bayesian Hierarchical Clustering with the Beta Coalescent
Yuening Hu, Jordan L Ying, Hal Daume III et al.